Post-doctoral Computational Geneticist (f / m / d)

Post-doctoral Computational Geneticist (f / m / d)

The mission of the Berlin Institute of Health at Charité (BIH) is medical translation: transferring biomedical research findings into novel approaches to personalized prediction, prevention, diagnostics and therapies and, conversely, using clinical observations to develop new research ideas. The aim is to deliver relevant medical benefits to patients and the population at large. The BIH was founded in 2013 and is funded 90 percent by the Federal Ministry of Education and Research (BMBF) and 10 percent by the State of Berlin. Since 2021 the BIH has been integrated into Charité as its so-called third pillar.

Starting from now limited for 21 months the BIH is looking for a

Post-doctoral Computational Geneticist (f / m / d)

This role will be part of a bilateral grant from the DZHK / BHF to collaboratively deliver new proteogenomic insights for cardiovascular diseases with the BHF CEU at the University of Cambridge. Close working with and visits to these institutions are encouraged as a part of this role. The BIH group is further affiliated with the Queen Mary University London, UK, and is building links to the Wellcome Centre for Human Genetics and Big Data Institute as part of the Berlin University Alliance\’s international strategic partnership with the University of Oxford, UK. The post is initially limited to 21 months, but extension is intended contingent on funding. The successful candidate will lead high profile scientific publications, represent the team in national and international collaborations and meetings, and contribute to the supervision of junior researchers.

Responsibilities:

• Development of computational workflows for processing and analysis of large-scale genome sequencing efforts from the UK Biobank or Genes & Health, in particular variant prioritization strategies and statistical workflows for rare and structural variant calling and analysis
• Management of large phenotypic datasets for genetic analysis, including outcome derivation from electronic health records
• Preparation of scientific publications
• Integration of different types of ‘omic’ data for causal interference and prioritization of drug targets and disease mechanisms
• Training and supervision of Master or PhD students within the group in molecular epidemiology

Your Profile:

• Completed PhD in statistical genetics, genetic epidemiology, or a closely related discipline, with a proven track record to write and publish scientific articles
• Extensive, demonstrable experience in several of the following areas:

• Generation and/or analysis of high-throughput genetic and genomic data
• Genome-scale association analyses using whole-genome or whole-exome sequencing data
• High-level expertise in computational genetics, e.g. variant annotation and structural variant calling
• Extensive, demonstrable experience with principal programming and scripting languages (e.g. R or Python)
• Aptitude for biological inference and clinical translation
• Desirable, useful skills and experience include all of the following: metabolomic and proteomic data and technologies, Bayesian statistics, including fine-mapping, Mendelian randomisation, cloud computing services, electronic health record linkage
• Fluent written and spoken English

We Offer:

• A varied job in a forward-looking research institute
• Flat hierarchies and short decision-making processes
• Very good opportunities for further education and training
• A limited full-time position (min. 39h/week)
• Remuneration up to TVöD VKA-K E13, taking into account personal requirements.
• Additional benefits customary in the public sector (e.g. annual bonus, VBL)
• 30 vacation days per year (with a five-day week) and up to 24 floating days per year
• Flexible working hours and option to work mobile for a better work-life balance
• Very accessible and attractive workplace at the Rahel Hirsch Center for Translational Medicine, Luisenstr. 65, 10117 Berlin

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